Abstract This thesis focuses on two important challenges in wireless downlink transmission: multi-user (MU) precoder design and scheduling of users over time, frequency, and spatial resources at any given instant. Data streams intended for different users are transmitted by a multiple-input multiple-output (MIMO) multi-antenna orthogonal frequency division multiplexing (OFDM) system. The transmit precoders are designed jointly across space-frequency resources to minimize the number of backlogged packets waiting at the coordinating base stations (BSs), thereby implicitly performing user scheduling. Then the problem of multicast beamformer design is considered wherein a subset of users belonging to a multicasting group are served by a common group-specific data. The design objective is to either minimize the transmit power for a guaranteed quality-of-service, or to maximize the minimum achievable rate among users for a given transmit power. Unlike existing techniques, the proposed design utilizes both the spatial and frequency resources jointly while designing multi-group beamformers. As an extension to coordinated precoding, the problem of beamformer design for cloud radio access network is considered wherein beamformers are designed centrally, quantized and sent along with data to the respective BSs via backhaul. Since the users can be served by multiple BSs, beamformer design becomes a nonconvex combinatorial problem. Unlike existing solutions, beamformer overhead is also included in the backhaul utilization along with the associated data. As the number of antennas increases, backhaul utilization is dominated by the beamformers. Thus, to reduce the overhead, two techniques are proposed: varying the quantization precision, and reducing the number of active antennas used for transmission. Finally, to reduce the complexity involved in the design of joint space- frequency approach, a two-step procedure is proposed, where a MU-MIMO scheduling algorithm is employed to find a subset of users for each scheduling block. The precoders are then designed only for the chosen users, thus reducing the complexity without compromising much on the throughput. In contrast to the null-space-based existing techniques, a low-complexity scheduling algorithm is proposed based on vector projections. The real-time performance of all the schedulers are evaluated by implementing them on both Xilinx ZYNQ-ZC702 system-on-chip (SoC) and TI TCI6636K2H multi-core SoC. / Tiivistelmä Tässä väitöskirjassa keskitytään kahteen tärkeään langattoman tiedonsiirron haasteeseen alalinkkilähetyksissä: usean käyttäjän (MU) esikooderisuunnitteluun ja käyttäjien skedulointiin aika-, taajuus- ja tilaresurssien yli. Eri käyttäjille tarkoitettuja datavirtoja lähetetään käyttämällä monitulo-monilähtötekniikkaa (MIMO) yhdistettynä monikantoaaltomodulointiin (OFDM). Lähettimien esikooderit suunnitellaan yhteisesti tila- ja taajuusresurssien yli, jotta keskenään yhteistoiminnallisten tukiasemien jonossa olevien pakettien määrää voitaisiin minimoida samalla kun tehdään epäsuorasti käyttäjien skedulointia. Tämän jälkeen työssä paneudutaan monilähetysten (multicast) keilanmuodostussuunnitteluun, jossa monilähetysryhmään kuuluvien käyttäjien alijoukolle lähetetään yhteistä ryhmäspesifistä dataa. Suunnittelun päämääränä on joko minimoida kokonaislähetysteho tietyllä palvelunlaatuvaatimuksella tai maksimoida pienin saavutettavissa oleva siirtonopeus käyttäjien joukossa tietyllä lähetysteholla. Toisin kuin olemassa olevat menetelmät, ehdotetussa mallissa käytetään yhteisesti sekä aika- että taajuusresursseja usean ryhmän keilanmuodostusta suunniteltaessa. Laajennuksena yhteistoiminnalliselle esikoodaukselle, väitöskirjassa käsitellään myös keilanmuodostusta pilvipohjaisessa radioliityntäverkkoarkkitehtuurissa. Keilanmuodostajat suunnitellaan keskitetysti, kvantisoidaan ja lähetetään datan mukana tukiasemille käyttäen runkoverkkoyhteyttä. Koska käyttäjiä voidaan palvella usealta tukiasemalta, keilanmuodostussuunnittelu muuttuu ei-konveksiksi kombinatoriseksi ongelmaksi. Toisin kuin olemassa olevissa ratkaisuissa, ehdotettu malli sisällyttää käyttäjien datan lisäksi keilanmuodostajien resursoinnin tarpeen runkoverkkoon. Tukiaseman antennien määrän lisääntyessä, keilanmuodostajien osuus runkoverkon käyttöasteesta kasvaa suureksi. Jotta keilanmuodostajien aiheuttamaa ylimääräistä tiedonsiirtotarvetta voitaisiin minimoida, esitellään kaksi tekniikkaa: kvantisointitarkkuuden muunteleminen sekä lähetykseen käytettävien aktiivisten antennien määrän vähentäminen. Lopuksi, jotta yhdistetyn tila-taajuussuunnittelun aiheuttamaa kompleksisuutta saataisiin vähennettyä, ehdotetaan kaksivaiheista menetelmää. MU-MIMO skedulointialgoritmin avulla etsitään ensin alijoukko käyttäjiä jokaiselle skedulointilohkolle. Esikooderit suunnitellaan vain valituille käyttäjille, mikä vähentää kompleksisuutta, heikentämättä suorituskykyä kuitenkaan olennaisesti. Poiketen nolla-avaruuteen perustuvista tekniikoista, esitetään yksinkertainen vektoriprojektioihin perustuva skeduleri. Kaikkien skedulerien reaaliaikasuorituskykyä on arvioitu toteuttamalla ne ohjelmoitavilla Xilinx ZYNQ-ZC702 system-on-chip (SoC) ja TI TCI6636K2H moniydinalustoilla.

Les robots flexibles sont de plus en plus utilisés dans les applications pratiques. Ces robots sont caractérisés par une conception mécanique légère, réduisant ainsi leur encombrement, leur consommation d’énergie et améliorant leur sécurité. Cependant, la présence de vibrations transitoires rend difficile un contrôle précis de la trajectoire de ces systèmes. Cette thèse est précisément consacrée à l’asservissement en position des manipulateurs flexibles dans les espaces articulaire et opérationnel. Des méthodes de commande avancées, basées sur des outils de la commande robuste et de l’optimisation convexe, ont été proposées. Ces méthodes font en particulier appel à la théorie des systèmes linéaires à paramètres variants (LPV) et aux inégalités matricielles linéaires (LMI). En comparaison avec des lois de commande non-linéaires disponibles dans la littérature, les lois de commande LPV proposées permettent de considérerdes contraintes de performance et de robustesse de manière simple et systématique. L’accent est porté dans notre travail sur la gestion appropriée de la dépendance paramétrique du modèle LPV, en particulier les dépendances polynomiale et rationnelle. Des simulations numériques effectuées dans des conditions réalistes, ont permis d’observer une meilleure robustesse de la commande LPV par rapport à la commande non-linéaire par inversion de modèle face aux bruits de mesure, aux excitations de haute fréquence et aux incertitudes de modèle. / Flexible robots are becoming more and more common in practical applications. This type of robots is characterized by the use of lightweight materials, which allows reducing their size, their power consumption and improves their safety. However, an accurate trajectory tracking of these systems is difficult to achieve because of the transient vibrations they undergo. This PhD thesis work is particularly devoted to the position control of flexible robotic manipulators at the joint and end-effector levels. Advanced control methods, based on some tools of the robust control theory and convex optimization, have been proposed. These methods are based on the theory of Linear Parameter Varying (LPV) systems and Linear Matrix Inequalities (LMI). Compared to some nonlinear control laws available in the literature that involve model inversion, theproposed LPV control laws make it possible to consider performance and robustness constraints in a simple and systematic manner. Our work particularly emphasizes on the appropriate management of the parametric dependence of the LPV model, especially the polynomial and rational dependences. Numerical simulations carried out in realistic operating conditions have shown a better robustness of the LPV control compared to the inversion-based nonlinear control withrespect to measurement noise, high frequency inputs and model uncertainties.

Nous considérons le problème de débruitage d'un signal ou d'une image observés dans le bruit gaussien. Dans ce problème les estimateurs linéaires classiques sont quasi-optimaux quand l'ensemble des signaux, qui doit être convexe et compact, est connu a priori. Si cet ensemble n'est pas spécifié, la conception d'un estimateur adaptatif qui ``ne connait pas'' la structure cachée du signal reste un problème difficile. Dans cette thèse, nous étudions une nouvelle famille d'estimateurs des signaux satisfaisant certains propriétés d'invariance dans le temps. De tels signaux sont caractérisés par leur structure harmonique, qui est généralement inconnu dans la pratique.Nous proposons des nouveaux estimateurs capables d'exploiter la structure harmonique inconnue du signal è reconstruire. Nous démontrons que ces estimateurs obéissent aux divers "inégalités d'oracle," et nous proposons une implémentation algorithmique numériquement efficace de ces estimateurs basée sur des algorithmes d'optimisation de "premier ordre." Nous évaluons ces estimateurs sur des données synthétiques et sur des signaux et images réelles. / We consider the problem of denoising a signal observed in Gaussian noise.In this problem, classical linear estimators are quasi-optimal provided that the set of possible signals is convex, compact, and known a priori. However, when the set is unspecified, designing an estimator which does not ``know'' the underlying structure of a signal yet has favorable theoretical guarantees of statistical performance remains a challenging problem. In this thesis, we study a new family of estimators for statistical recovery of signals satisfying certain time-invariance properties. Such signals are characterized by their harmonic structure, which is usually unknown in practice. We propose new estimators which are capable to exploit the unknown harmonic structure of a signal to reconstruct. We demonstrate that these estimators admit theoretical performance guarantees, in the form of oracle inequalities, in a variety of settings.We provide efficient algorithmic implementations of these estimators via first-order optimization algorithm with non-Euclidean geometry, and evaluate them on synthetic data, as well as some real-world signals and images.

Acquises dans plusieurs centaines de bandes spectrales contiguës, les images hyperspectrales permettent d'analyser finement la composition d'une scène observée. En raison de la résolution spatiale limitée des capteurs utilisés, le spectre d'un pixel d'une image hyperspectrale résulte de la composition de plusieurs signatures associées à des matériaux distincts. À ce titre, le démélange d'images hyperspectrales vise à estimer les signatures des différents matériaux observés ainsi que leur proportion dans chacun des pixels de l'image. Pour cette analyse, il est d'usage de considérer qu'une signature spectrale unique permet de décrire un matériau donné, ce qui est généralement intrinsèque au modèle de mélange choisi. Toutefois, la signature d'un matériau présente en pratique une variabilité spectrale qui peut être significative d'une image à une autre, voire au sein d'une même image. De nombreux paramètres peuvent en être cause, tels que les conditions d'acquisitions (e.g., conditions d'illumination locales), la déclivité de la scène observée ou des interactions complexes entre la lumière incidente et les éléments observés. À défaut d'être prises en compte, ces sources de variabilité perturbent fortement les signatures extraites, tant en termes d'amplitude que de forme. De ce fait, des erreurs d'estimation peuvent apparaître, qui sont d'autant plus importantes dans le cas de procédures de démélange non-supervisées. Le but de cette thèse consiste ainsi à proposer de nouvelles méthodes de démélange pour prendre en compte efficacement ce phénomène. Nous introduisons dans un premier temps un modèle de démélange original visant à prendre explicitement en compte la variabilité spatiale des spectres purs. Les paramètres de ce modèle sont estimés à l'aide d'un algorithme d'optimisation sous contraintes. Toutefois, ce modèle s'avère sensible à la présence de variations spectrales abruptes, telles que causées par la présence de données aberrantes ou l'apparition d'un nouveau matériau lors de l'analyse d'images hyperspectrales multi-temporelles. Pour pallier ce problème, nous introduisons une procédure de démélange robuste adaptée à l'analyse d'images multi-temporelles de taille modérée. Compte tenu de la dimension importante des données étudiées, notamment dans le cas d'images multi-temporelles, nous avons par ailleurs étudié une stratégie d'estimation en ligne des différents paramètres du modèle de mélange proposé. Enfin, ce travail se conclut par l'étude d'une procédure d'estimation distribuée asynchrone, adaptée au démélange d'un grand nombre d'images hyperspectrales acquises sur une même scène à différents instants. / Acquired in hundreds of contiguous spectral bands, hyperspectral (HS) images have received an increasing interest due to the significant spectral information they convey about the materials present in a given scene. However, the limited spatial resolution of hyperspectral sensors implies that the observations are mixtures of multiple signatures corresponding to distinct materials. Hyperspectral unmixing is aimed at identifying the reference spectral signatures composing the data -- referred to as endmembers -- and their relative proportion in each pixel according to a predefined mixture model. In this context, a given material is commonly assumed to be represented by a single spectral signature. This assumption shows a first limitation, since endmembers may vary locally within a single image, or from an image to another due to varying acquisition conditions, such as declivity and possibly complex interactions between the incident light and the observed materials. Unless properly accounted for, spectral variability can have a significant impact on the shape and the amplitude of the acquired signatures, thus inducing possibly significant estimation errors during the unmixing process. A second limitation results from the significant size of HS data, which may preclude the use of batch estimation procedures commonly used in the literature, i.e., techniques exploiting all the available data at once. Such computational considerations notably become prominent to characterize endmember variability in multi-temporal HS (MTHS) images, i.e., sequences of HS images acquired over the same area at different time instants. The main objective of this thesis consists in introducing new models and unmixing procedures to account for spatial and temporal endmember variability. Endmember variability is addressed by considering an explicit variability model reminiscent of the total least squares problem, and later extended to account for time-varying signatures. The variability is first estimated using an unsupervised deterministic optimization procedure based on the Alternating Direction Method of Multipliers (ADMM). Given the sensitivity of this approach to abrupt spectral variations, a robust model formulated within a Bayesian framework is introduced. This formulation enables smooth spectral variations to be described in terms of spectral variability, and abrupt changes in terms of outliers. Finally, the computational restrictions induced by the size of the data is tackled by an online estimation algorithm. This work further investigates an asynchronous distributed estimation procedure to estimate the parameters of the proposed models.

[pt] Neste trabalho, quatro métodos projetados especificamente para a estimação de sistemas esparsos são originalmente elaborados e apresentados. São eles: Encolhimentos Sucessivos, Expansões Sucessivas, Minimização da Norma l1 e Ajuste Automático do fator de regularização do Custo LS. Os quatro métodos propostos baseiam-se na técnica de estimação de sistemas lineares e invariantes no tempo pelo critério dos mínimos quadrados, universalmente conhecida por sua denominação em inglês - Least Squares (LS) Estimation, e incorporam técnicas relacionadas a otimização convexa e à teoria de compressive sensing. Os resultados obtidos em simulações mostram que os métodos em questão têm desempenho superior que a estimação LS convencional e que o algoritmo Recursive Least Squares (RLS) com regularização convexa denominado l1-RLS, em muitos casos alcançando o desempenho ótimo apresentado pelo método de estimação LS Oráculo, no qual o suporte da resposta ao impulso em tempo discreto do sistema estimado é conhecido a priori. Além disso, os métodos propostos apresentam custo computacional menor que do algoritmo l1-RLS. / [en] In this thesis, four methods specifically designed for sparse systems estimation are originally developed and presented, which were called here: Relaxations method, Successive Expansions method, l1-norm Minimization method and Automatic Adjustment of the Regularization Factor method. The four proposed methods are based on the Least Squares (LS) Estimation method and incorporate techniques related to convex optimization and to the theory of compressive sensing. The simulation results show that the proposed methods herein present superior performance than the ordinary LS estimation method and the Recursive Least Squares (RLS) with convex regularization method (l1-RLS), in many cases achieving the same optimal performance presented by the LS Oracle method. Furthermore, the proposed methods demand lower computational cost than the l1-RLS method.

Orientador: Michel Daoud Yacoub / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-10T01:21:53Z (GMT). No. of bitstreams: 1 CaceresZuniga_YusefRafael_D.pdf: 1196886 bytes, checksum: b589961266e398a3fd22bfd7b30719e4 (MD5) Previous issue date: 2007 / Resumo: Nesta tese, estuda-se o problema da alocação de potência através de duas abordagens: estocástica e robusta, sendo os ganhos do canal, que descrevem o estado do sistema de comunicações sem fio, parcialmente observados pelo decisor. Na abordagem estocástica, considera-se que os ganhos do canal são variáveis aleatórias, que representam a variação rápida do sinal de rádio. Nesse contexto, reformula-se o índice de desempenho do sistema através do CVaR (Conditional. Value-at-Risk). Na abordagem robusta, considera-se que os ganhos do canal e o ruído pertencem a um determinado conjunto convexo. Em ambas as abordagens, a solução ótima é obtida em termos de um problema de otimização convexa. Adicionalmente, na abordagem estocástica, apresenta-se um algoritmo recursivo e distribuído, que converge para uma solução subótima, quando o ruído é nulo e a potência transmitida é limitada tanto superior como inferiormente. Também mostra-se que, em um sistema onde os ganhos do canal coincidem com o seu valor esperado, esse algoritmo converge para a soluçãã ótima quando a qualidade do enlace é muito maior que a mínima requerida / Abstract: This thesis deals with the power allocation problem under the stochastic and robust approaches, where the channel gains describe the wireless communication system state and are partially known by the controller. The stochastic approach considers the channel gains as random variables which represent the fast fading of the radio signal. Under these settings, the system performance index is reformulated using CVaR (Conditional Value-at-Risk). The robust approach considers that the channels gains and noise belong to a determined convex set. ln both approaches, the optimal solution is determined in terms of a convex optimization problem. Additionally, under the stochastic approach, a recursive and distributed algorithm is presented which converges to its suboptimal solution when noise is null and the transmitted power is upper and lower bounded. It is also show that this algorithm converges to its optimal solution when the link quality is much greater than the minimum required quality in a system where the channels gains match its expected value / Doutorado / Telecomunicações e Telemática / Doutor em Engenharia Elétrica

Cette thèse consiste à étudier l'organisation du système de contrôle des voies métaboliques des bactéries afin de dégager des propriétés systémiques révélant son fonctionnement. Dans un premier temps, nous montrons que le contrôle des voies métaboliques est hautement structuré et peut se décomposer en modules fortement découplés en régime stationnaire. Ces modules possèdent des propriétés mathématiques remarquables ayant des conséquences importantes en biologie. Cette décomposition, basée intrinsèquement sur la vision système de l'Automatique, offre un cadre théorique formel général d'analyse du contrôle des voies métaboliques qui s'est révélé effectif pour analyser des données expérimentales. dans un deuxième temps, nous nous intéressons aux raisons possibles de l'émergence de cette structure de contrôle similaire. Nous identifions un ensemble de contraintes structurelles agissant au niveau de la répartition d'une ressource commune, les protéines, entre les processus cellulaires. Respecter ces contraintes pour un taux de croissance donné conduit à formaliser et résoudre un problème d'optimisation convexe non différentiable, que nous appelons Resource balance Analysis. Ce problème d'optimisation se résout numériquement à l'échelle de la bactérie grâce à un problème de Programmation Linéaire équivalent. plusieurs propriétés sont déduites de l'analyse théorique du critère obtenu. Tout d'abord, le taux de croissance est structurellement limité par la répartition d'une quantité finie de protéines entre les voies métaboliques et les ribosomes. Ensuite, l'émergence des modules dans les voies métaboliques provient d'une politique générale d'économie en protéines chez la bactérie pour gagner du taux de croissance. Certaines stratégies de transport bien connues comme la répression catabolique ou la substitution de transporteurs haute/basse affinités sont prédites par notre méthode et peuvent alors être interprétées comme le moyen de maximiser la croissance tout en minimisant l'investissement en protéines. / This thesis consist in studying the organization of the control system of metabolic pathways of bacteria to identify systemic properties revealing its operation. At first, we show that control of metabolic pathways is highly structured and can be decomposed into modules strongly decoupled in steady-state. These modules are defined by their singular mathematical properties having important implications in biology. This decomposition, based inherently on the system outlook of automatic control, offers a formal theoretical analysis of general control of metabolic pathways, which has been effective in analysing experimental data. In a second step, we consider the possible reasons for the emergence of this modular control structure. We identify a set of structural constraints acting at the distribution of a common resourc, the proteins between cellular processes. Satisfying these constraints for a given growth rate leads to formalize and to solve a non-differentiable convex optimization problem, that we call Resource Balance Analysis. This optimization problem is solved numerically at the scale of the bacteria through an equivalent linear programming problem. Several properties are derived from theoretical analysis of the obtained criterion. Firts, the growth rate is structurally limited by the distribution of a finite amount of proteines between the metabolic pathways and the ribosomes. Second, the emergence of modules in metabolic pathways arises from a policy of economy in proteins in the bacterium to increase the growth rate. Some well known transport strategies such as catabolite repression of the substitution between low/highaffinity transporters are predicted by our methods and could consequently be interpretd as ways to maximize growth while minimizing investment in proteins.

No description available.

<div>Optimization of atmospheric flight control has long been performed on the ground, prior to mission flight due to large computational requirements used to solve non-linear programming problems. Onboard trajectory optimization enables the creation of new reference trajectories and updates to guidance coefficients in real time. This thesis summarizes the methods involved in solving optimal control problems in real time using convexification and Sequential Convex Programming (SCP). The following investigation provided insight in assessing the use of state of the art SCP optimization architectures and convexification of the hypersonic equations of motion[ 1 ]–[ 3 ] with different control schemes for the purposes of enabling on-board trajectory optimization capabilities.</div><div>An architecture was constructed to solve convexified optimal control problems using direct population of sparse matrices in triplet form and an embedded conic solver to enable rapid turn around of optimized trajectories. The results of this show that convexified optimal control problems can be solved quickly and efficiently which holds promise in autonomous trajectory design to better overcome unexpected environments and mission parameter changes. It was observed that angle of attack control problems can be successfully convexified and solved using SCP methods. However, the use of multiple coupled controls is not guaranteed to be successful with this method when they act in the same plane as one another. The results of this thesis demonstrate that state of the art SCP methods have the capacity to enable onboard trajectory optimization with both angle of attack control and bank angle control schemes.</div><div><br></div>

The master's thesis deals with the problem of restoring a block of missing samples in a digital audio signal. This problem is formulated as an optimization task, which seeks the sparsest time-frequency representation of a signal within the set of feasible reconstructed signals. Several particular formulations are discussed, namely the analyzing and the synthesizing model, both for convex and non-convex approaches. Suitable algorithms are proposed for solving these formulations, and in the convex case, the method is further enhanced by various procedures to compensate for the energy drop in the inpainted signal segment. The proposed algorithms are tested on real recordings, and their performance is shown to be competitive with the state-of-the-art.